Summary
History matching of a reservoir model is always a difficult task. In some
fields, we can use time-lapse (4D) seismic data to detect production-induced
changes as a complement to more conventional production data. In seismic
history matching, we predict these data and compare to observations. Observed
time-lapse data often consist of relative measures of change, which require
normalization. We investigate different normalization approaches, based on
predicted 4D data, and assess their impact on history matching.
We apply the approach to the Nelson field in which four surveys are
available over 9 years of production. We normalize the 4D signature in a number
of ways. First, we use predictions of 4D signature from vertical wells that
match production, and we derive a normalization function. As an alternative, we
use crossplots of the full-field prediction against observation. Normalized
observations are used in an automatic-history-matching process, in which the
model is updated. We analyze the results of the two normalization approaches
and compare against the case of just using production data.
The result shows that when we use 4D data normalized to wells, we obtain 49%
reduced misfit along with 36% improvement in predictions. Also over the whole
reservoir, 8 and 7% reduction of misfits for 4D seismic are obtained in history
and prediction periods, respectively. When we use only production data, the
production history match is improved to a similar degree (45%), but in
predictions, the improvement is only 25% and the 4D seismic misfit is 10%
worse.
Finding the unswept areas in the reservoir is always a challenge in
reservoir management. By using 4D data in history matching, we can predict
reservoir behavior better and identify regions of remaining oil or better.
© 2011. Society of Petroleum Engineers
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History
- Original manuscript received:
5 November 2010
- Meeting paper published:
15 June 2010
- Revised manuscript received:
26 February 2011
- Manuscript approved:
29 March 2011
- Published online:
21 September 2011
- Version of record:
13 October 2011
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